The present invention generally relates to systems for processing medical data research requests, and more specifically, to cognitive systems for allocating medical data access permissions using historical correlations.
The process of receiving medical data for research is often slow and riddled with error. To get medical data, a medical researcher often needs to write up a data request, either manually or in electronic form, and submit it to an institution's internal review board (IRB) for approval. The IRB then reviews the data request and after upwards of a month, either approves or denies the request. Upon approval, the request is submitted to a server to retrieve the data and/or send to the institution's data administrator (or an individual with similar data provisioning responsibilities) who then manually locates the data to which he thinks the request refers. This data is collected by the data administrator, and/or server, then given to the requestor. If, however, the requestor comes to realize that additional data is needed for the requestor's research, the requestor would need to re-submit a data request to the IRB and repeat the process.